Sample.EF: Sample Fitted Exponential Family
In zrmacc/LFDR: Local False Discovery Rate Estimation
Description
Usage
Arguments
Value
Description
Sampling via the accept-reject algorithm. The proposal distribution
is taken as normal, with the option to specify the mean and variance.
Usage
1
2
Arguments
z
Observations.
f
Density to sample.
m
Proposal mean.
v
Proposal variance.
n
Target number of sample to obtain.
parallel
Run in parallel? Must register parallel backend first.
maxit
Maximum number of accept-reject iterations.
Value
Vector of realizations from the mixture density.
zrmacc/LFDR documentation built on May 3, 2019, 9:01 p.m.
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Description Usage Arguments Value
Description
Sampling via the accept-reject algorithm. The proposal distribution is taken as normal, with the option to specify the mean and variance.
Usage
1 2 |
Arguments
z |
Observations. |
f |
Density to sample. |
m |
Proposal mean. |
v |
Proposal variance. |
n |
Target number of sample to obtain. |
parallel |
Run in parallel? Must register parallel backend first. |
maxit |
Maximum number of accept-reject iterations. |
Value
Vector of realizations from the mixture density.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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